AI/ML Engineer, Generative Previsualisation

The role This role is focused on turning scripts, creative briefs, visual references, moodboards, characters, locations, and production intent into useful visual outputs for directors, producers, and creative teams. It is not a pure research role, and it is not a generic chatbot role. We need someone who can experiment with generative image/video models, structure training and evaluation data, improve visual consistency, and help turn model workflows into practical product features. You will work closely with the founding team, product engineering, and production users to build AI systems that support real creative decision-making. What you'll do Build and evaluate AI workflows for script-to-scene and script-to-shot previsualisation Work with generative image and video models, multimodal models, and LLMs Design datasets from scripts, briefs, visual references, storyboards, shot lists, moodboards, frames, and production metadata Experiment with fine-tuning, LoRA/adapters, prompting, retrieval, and reference-conditioning workflows Improve consistency across characters, locations, style, mood, framing, and scene continuity Explore workflows for generating visual options that are useful to directors, producers, and creative teams Evaluate generated outputs for creative usefulness, consistency, quality, latency, and cost Collaborate with full-stack engineers to integrate AI workflows into YAM Help decide when to use existing models, fine-tuning, custom datasets, third-party APIs, or open-source model pipelines Build repeatable evaluation methods so we can improve model outputs over time What we're looking for 3+ years of experience in machine learning, applied AI, computer vision, generative AI, or AI engineering Strong Python skills Experience with image generation, video generation, multimodal AI, or visual-language models Familiarity with model fine-tuning, LoRA, adapters, embeddings, or conditioning workflows Experience working with messy real-world data and turning it into usable training or evaluation datasets Ability to prototype quickly while thinking about production constraints Practical understanding of model limitations, hallucinations, consistency issues, latency, and cost Strong problem-solving ability and clear communication Interest in film, content production, creative tools, or visual storytelling Nice to have Experience with Stable Diffusion, Flux, ComfyUI, Runway, Kling, V, Sora-style workflows, or similar generative tools Experience with ControlNet, IP-Adapter, reference conditioning, character consistency, style transfer, or visual continuity workflows Experience with image/video understanding, shot analysis, scene parsing, or visual metadata extraction Experience with LLMs, structured outputs, RAG, or agentic workflows Experience building AI products beyond notebooks and demos Experience in film, advertising, animation, storyboarding, previsualisation, creative tooling, or content production Experience deploying AI systems into production environments You'll thrive here if You are excited by the idea of AI helping creative teams visualise ideas earlier You care about whether generated outputs are actually useful, not just impressive You enjoy experimenting with models but can stay grounded in product needs You can work with ambiguity and turn rough creative workflows into structured systems You are pragmatic about using the best available tools instead of reinventing everything You want to work at the intersection of generative AI, storytelling, and production workflows How to apply Send your application to karen@gengis.ai and include: LinkedIn, GitHub, portfolio, or relevant project links One AI/generative model project you have built or contributed to Any examples of image/video generation, fine-tuning, LoRA, visual consistency, multimodal AI, or model evaluation work A short note on why this role interests you